Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-26T19:16:37.113Z Has data issue: false hasContentIssue false
  • English
  • Français

Who eats four or more servings of fruit and vegetables per day? Multivariate classification tree analysis of data from the 1998 Survey of Lifestyle, Attitudes and Nutrition in the Republic of Ireland

Published online by Cambridge University Press:  02 January 2007

Sharon Friel ,
John Newell  and
Cecily Kelleher
Sharon Friel*
Affiliation:
Centre for Health Promotion Studies, National University of Ireland, Block T, Distillery Road, Galway, Republic of Ireland
John Newell
Affiliation:
Department of Mathematics, National University of Ireland, Galway, Republic of Ireland
Cecily Kelleher
Affiliation:
Department of Epidemiology and Public Health Medicine, University College Dublin, Republic of Ireland
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective

To identify, using the novel application of multivariate classification trees, the socio-economic, sociodemographic and health-related lifestyle behaviour profile of adults who comply with the recommended 4 or more servings per day of fruit and vegetables.

Design

Cross-sectional 1998 Survey of Lifestyle, Attitudes and Nutrition.

Setting

Community-dwelling adults aged 18 years and over on the Republic of Ireland electoral register.

Subjects

Six thousand five hundred and thirty-nine (response rate 62%) adults responded to a self-administered postal questionnaire, including a semi-quantitative food-frequency questionnaire.

Results

The most important determining factor of compliance with the fruit and vegetable dietary recommendations was gender. A complex constellation of sociodemographic and socio-economic factors emerged for males whereas the important predictors of 4 or more servings of fruit and vegetable consumption among females were strongly socio-economic in nature. A separate algorithm was run to investigate the importance of health-related lifestyle and other dietary factors on compliance with the fruit and vegetable recommendations. Following an initial split on compliance with dairy recommendations, a combination of non-dietary behaviours showed a consistent pattern of healthier options more likely to lead to compliance with fruit and vegetable recommendations. There did, however, appear to be a compensatory element between the variables, particularly around smoking, suggesting the non-existence of an exclusive lifestyle for health risk.

Conclusions

Material and structural influences matter very much for females in respect to compliance with fruit and vegetable recommendations. For males, while these factors are important they appear to be mediated through other more socially contextual-type factors. Recognition of the role that each of these factors plays in influencing dietary habits of men and women has implications for the manner in which dietary strategies and policies are developed and implemented.

Keywords

Multivariate analysisClassification treesDietSocial variation
Type
Research Article
Information
Public Health Nutrition , Volume 8 , Issue 2 , April 2005 , pp. 159 - 169
Copyright
Copyright © The Authors 2005

References

1Beer-Borst, S, Hercberg, S, Morabia, A, Bernstein, MS, Galan, P, Galasso, R, et al. Dietary patterns in six European populations: results from EURALIM, a collaborative European data harmonisation and information campaign. European Journal of Clinical Nutrition 2000; 54: 253–62.CrossRefGoogle Scholar
2James, WPT, Nelson, M, Ralph, A, Leather, S. The contribution of nutrition to inequalities in health. British Medical Journal 1997; 314: 1545–9.CrossRefGoogle ScholarPubMed
3Leather, S. Fruit and vegetables: consumption patterns and health consequences. British Food Journal 1995; 97: 10–17.CrossRefGoogle Scholar
4McElduff, P, Dobson, AJ. Trends in coronary heart disease – has the socioeconomic differential changed? Australian and New Zealand Journal of Public Health 2000; 24: 465–73.CrossRefGoogle ScholarPubMed
5Davey Smith, G, Marmot, M. Trends in mortality in Britain: 1920–1986. Annals of Nutrition & Metabolism 1991; 35(Suppl. 1): 53–63.Google Scholar
6Milligan, RAK, Burke, V, Beilin, LJ, Dunbar, DL, Spencer, MJ, Balde, E, et al. Influence of gender and socioeconomic status on dietary patterns and nutrient intakes in 18 year old Australians. Australian and New Zealand Journal of Public Health 1998; 22: 485–93.CrossRefGoogle ScholarPubMed
7Billson, H, Pryer, JA, Nichols, R. Variation in fruit and vegetable consumption among adults in Britain. An analysis from the dietary and nutritional survey of British adults. European Journal of Clinical Nutrition 1999; 53: 946–52.CrossRefGoogle ScholarPubMed
8Popkin, BM, Siega-Riz, AM, Haines, PS. A comparison of dietary trends among racial and socioeconomic groups in the United States. New England Journal of Medicine 1996; 335: 716–20.CrossRefGoogle ScholarPubMed
9Mishra, G, Ball, K, Arbuckle, J, Crawford, D. Dietary patterns of Australian adults and their association with socioeconomic status: results from the 1995 National Nutrition Survey. European Journal of Clinical Nutrition 2002; 56: 687–93.CrossRefGoogle ScholarPubMed
10Roos, E, Lahelma, E, Virtanen, M, Prattala, R, Pietinen, P. Gender, socioeconomic status and family status as determinants of food behaviour. Social Science & Medicine 1998; 46: 1519–29.CrossRefGoogle ScholarPubMed
11Beaton, GH. Approaches to analysis of dietary data: relationship between planned analyses and choice of methodology. American Journal of Clinical Nutrition 1994; 59: 253S–61S.CrossRefGoogle ScholarPubMed
12Fidanza, F, Gentile, MA, Porrini, M. A self administered semiquantitative food frequency questionnaire with optical reading and its concurrent validation. European Journal of Epidemiology 1995; 11: 163–70.CrossRefGoogle ScholarPubMed
13Nutrition Advisory Group to the Department of Health (NAG). Recommendations for a Food and Nutrition Policy. Dublin: NAG, 1995.Google Scholar
14Willett, WC, Sacks, F, Trichopoulou, A, Drescher, G, Ferro-Luzzi, A, Helsing, E, et al. Mediterranean diet pyramid: a cultural model for healthy eating. American Journal of Clinical Nutrition 1995; 61: 1402S–6S.CrossRefGoogle ScholarPubMed
15Hermann-Kunz, E, Thamm, M. Dietary recommendations and prevailing food and nutrient intakes in Germany. British Journal of Nutrition 1999; 81: s61–9.CrossRefGoogle ScholarPubMed
16Hulshof, KFAM, Wedel, M, Lowik, MRH, Kok, FJ, Kistemaker, C, Hermus, RJJ, et al. Clustering of dietary variables and other lifestyle factors (Dutch Nutrition Surveillance System). Journal of Epidemiology and Community Health 1992; 46: 417–24.CrossRefGoogle Scholar
17Wirfalt, AKE, Jeffery, RW. Using cluster analysis to examine dietary patterns: nutrient intakes, gender and weight status differ across food pattern clusters. Journal of American Dietetic Association 1997; 97: 272–9.CrossRefGoogle ScholarPubMed
18Pryer, JA, Nichols, R, Elliott, P, Thakrar, B, Brunner, E, Marmot, M. Dietary patterns among a national random sample of British adults. Journal of Epidemiology and Community Health 2001; 51: 29–37.CrossRefGoogle Scholar
19Martikainen, P, Brunner, E, Marmot, M. Socioeconomic differences in dietary patterns among middle aged men and women. Social Science & Medicine 2003; 56: 1397–410.CrossRefGoogle ScholarPubMed
20McCann, SE, Weiner, J, Graham, S, Freudenheim, JL. Is principal components analysis necessary to characterise dietary behaviour in studies of diet and disease? Public Health Nutrition 2001; 4: 903–8.CrossRefGoogle ScholarPubMed
21Ursin, G, Ziegler, RG, Subar, A, Graubard, BI, Haile, RW, Hoover, R. Dietary patterns associated with a low fat diet in the National Health Examination Follow up Study: identification of potential confounders for epidemiological analyses. American Journal of Epidemiology 1993; 137: 916–27.CrossRefGoogle Scholar
22Breiman, LJH, Friedman, R, Olshen, A, Stone, CJ. Classification and Regression Trees. Monterey, CA: Wadsworth Inc.., 1984.Google Scholar
23Steinberg, D, Colla, P. CART: Tree-structured Non Parametric Data Analysis. San Diego, CA: Salford Systems, 1995.Google Scholar
24Bloch, DA, Segal, MR. Empirical comparison of approaches of forming strata: using classification trees to adjust for covariates. Journal of the American Statistical Association 1989; 84: 897–905.Google Scholar
25Friel, S, Kelleher, CC, Nolan, G, Harrington, J. Social diversity of Irish adults nutritional intake. European Journal of Clinical Nutrition 2003; 57: 865–75.CrossRefGoogle ScholarPubMed
26Riboli, E, Kaaks, R. The EPIC project: rationale and study design. International Journal of Epidemiology 1997; 26(Suppl. 1): s6–14.CrossRefGoogle ScholarPubMed
27Bingham, SA, Gill, C, Welch, A, Cassidy, A, Runswick, SA, Oakes, S, et al. Validation of the dietary assessment methods in the UK arm of EPIC using 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. International Journal of Epidemiology 1997; 26(Suppl. 1): s137–51.CrossRefGoogle ScholarPubMed
28Centre for Health Promotion Studies (CHPS). The National Health and Lifestyle Surveys (SLAN/HBSC). Galway: CHPS, National University of Ireland, 1999.Google Scholar
29Central Statistics Office. Census of the Population 1996. Dublin: The Stationery Office, 1996.Google Scholar
30Willett, WC. Issues in analysis and presentation of dietary data. In: Willett, WC, ed. Nutritional Epidemiology, 2nd ed. Oxford: Oxford University Press, 1998; 398–9.CrossRefGoogle Scholar
31Burley, V, Cade, J, Margetts, B, Thompson, R, Warm, D. Consensus Document on the Development, Validation and Utilisation of Food Frequency Questionnaires. Leeds/Southampton: Nuffield Institute for Health, University of Leeds & Institute of Human Nutrition, University of Southampton, 2000.Google Scholar
32Clarke, GM, Cooke, D. A Basic Course in Statistics, 4th ed. London: Arnold, 1998.Google Scholar
33Department of Health (DoH). Nutrition Health Promotion Framework for Action. Dublin: DoH, 1991.Google Scholar
34Hjorth, JSU. Computer Intensive Statistical Methods Validation, Model Selection, and Bootstrap. London: Chapman & Hall, 1994.Google Scholar
35Yates, AA. Process and development of dietary reference intakes: basis, need and application of recommended dietary allowances. Nutrition Reviews 1998; 56: s5–9.CrossRefGoogle ScholarPubMed
36Pryer, JA, Cook, A, Shetty, P. Identification of groups who report similar patterns of diet among a representative national sample of British adults aged 65 years of age or more. Public Health Nutrition 2001; 4: 787–95.CrossRefGoogle ScholarPubMed
37Johansson, L, Andersen, LF. Who eats 5 a day?: intake of fruit and vegetables among Norwegians in relation to gender and lifestyle. Journal of the American Dietetic Association 1998; 98: 689–91.CrossRefGoogle Scholar
38Schulze, MB, Hoffmann, K, Kroke, A, Boeing, H. Dietary patterns and their association with food and nutrient intake in the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam study. British Journal of Nutrition 2001; 85: 363–73.CrossRefGoogle ScholarPubMed
39Anderson, A, Hunt, K. Who are the healthy eaters? Eating patterns and health promotion in the west of Scotland. Health Education Journal 1992; 51: 3–10.CrossRefGoogle Scholar
40Blaxter, M. Health and Lifestyles. London: Tavistock/Routledge, 1990.CrossRefGoogle Scholar
41Schafer, RB, Schafer, E. Relationship between gender and food roles in the family. Journal of Nutrition Education 1989; 21: 119–26.CrossRefGoogle Scholar
42Johansson, L, Thelle, DS, Solvoll, K, Bjornboe, GEA, Drevon, CA. Healthy dietary habits in relation to social determinants and lifestyle factors. British Journal of Nutrition 1999; 81: 211–20.CrossRefGoogle ScholarPubMed
43Depatment of Health and Children. The National Health Promotion Strategy 2000–2005. Dublin: Stationery Office, 2000.Google Scholar
44Block, G, Subar, AF. Estimates of nutrient intake from a food frequency questionnaire: the 1987 national health interview survey. Journal of the American Dietetic Association 1992; 92: 969–77.CrossRefGoogle ScholarPubMed
45Johansson, L, Solvoll, K, Bjorneboe, GEA, Drevon, CA. Dietary habits among Norwegian men and women. Scandinavian Journal of Nutrition 1997; 41: 63–70.Google Scholar
46Patterson, RE, Kristal, AR, Tinker, LF, Carter, RA, Bolton, MP, Agurs-Collins, T. Measurement characteristics of the Women's Health Initiative food frequency questionnaire. Annals of Epidemiology 1999; 9: 178–87.CrossRefGoogle ScholarPubMed
47Hupkens, CLH, Knibbe, RA, Drop, MJ. Social class differences in women's fat and fibre consumption: a cross national study. Appetite 1997; 28: 131–49.CrossRefGoogle ScholarPubMed
48Rimm, EB, Giovannucci, EL, Stampfer, MJ, Colditz, GA, Litin, LB, Willett, W. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. American Journal of Epidemiology 1992; 135: 1114–26.CrossRefGoogle ScholarPubMed
49Willett, WC. Future directions in the development of food frequency questionnaires. American Journal of Clinical Nutrition 1994; 59: 171S–4S.CrossRefGoogle ScholarPubMed
50Harrington, J. Validation of food frequency questionnaire for national health and lifestyle survey. Minor thesis as part MA in Health Promotion, National University of Ireland, Galway, 1998.Google Scholar
51Phillips, DL, Clancy, KJ. Some effects of social desirability in survey studies. American Journal of Sociology 1972; 77: 921–38.CrossRefGoogle Scholar